论文标题
随机局部波动率模型和WEI-NORMAN分解方法
Stochastic Local Volatility models and the Wei-Norman factorization method
论文作者
论文摘要
在本文中，我们表明，可以通过WEI-NORMAN分解方法和谎言代数技术将时间依赖性的局部随机波动率（SLV）模型还原为自主PDE的系统。然后，我们将传统蒙特卡洛模拟的结果与所述技术获得的明确解决方案进行了比较。这种方法在文献中是新的，除了将非自主问题减少为自主问题外，还可以减少数值计算的时间。
In this paper, we show that a time-dependent local stochastic volatility (SLV) model can be reduced to a system of autonomous PDEs that can be solved using the Heat kernel, by means of the Wei-Norman factorization method and Lie algebraic techniques. Then, we compare the results of traditional Monte Carlo simulations with the explicit solutions obtained by said techniques. This approach is new in the literature and, in addition to reducing a non-autonomous problem into an autonomous one, allows for reduced time in numerical computations.
